Predicting GRE score range using TOEFL score based on Bayes' theorem

Jinxuan Fan

doi:10.1117/12.2628215

22 April 2022 Predicting GRE score range using TOEFL score based on Bayes' theorem

Jinxuan Fan

Proceedings Volume 12163, International Conference on Statistics, Applied Mathematics, and Computing Science (CSAMCS 2021); 1216325 (2022) https://doi.org/10.1117/12.2628215
Event: International Conference on Statistics, Applied Mathematics, and Computing Science (CSAMCS 2021), 2021, Nanjing, China

Abstract

Using Bayes Theorem and the conditional probability knowledge, this paper provides a method to predict a student’s GRE Score range based on his/her TOEFL Score. To locate the specific GRE range, a data set of 500 undergraduate students who have taken GRE and TOEFL exams is used as the statistics. This paper also borrows the statistics from the official website as the prior probabilities. The result shows that not only is there a positive relationship between the scores of the two exams, polarization also occurs regarding the two standardized exams scores. However, since the data set is retrieved from only one single spot, the reliability and universality are yet to be tested. A combination of more data sets obtained from different sites may help improve the prediction accuracy.

Citation Download Citation

Jinxuan Fan "Predicting GRE score range using TOEFL score based on Bayes' theorem", Proc. SPIE 12163, International Conference on Statistics, Applied Mathematics, and Computing Science (CSAMCS 2021), 1216325 (22 April 2022); https://doi.org/10.1117/12.2628215

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